Should You Trust AI For your Content Marketing Strategy?

Artificial Intelligence is everywhere you look – and you might not even realise it. Think about it, when you’re browsing through Netflix looking for a movie after a long day of work, you’re getting little “rating scores” at the side of each title to help you pick films that might appeal to you. When you’re checking your LinkedIn feed, you’re getting news that’s relevant to your industry, and interests.

After you’re done getting ready on a morning, you can tell your phone to set up a meeting for later in the day on your behalf and use voice activation to play your favourite playlist, while Apple maps tells you how long it’s going to get to reach the train station. Everywhere you go, the digital world follows – but should it be in your content marketing strategy?

Insights Drive Business

It’s safe to say that new approaches are changing the way we invest in marketing online. We now have automated solutions for connecting with new leads through emails and providing them with dynamic content. At the same time, chat bots are making it simpler for companies to connect with their audience at any time of day.

One important thing to note is that as the buying process has changed, companies are beginning to use content as a way of attracting, engaging, and converting consumers. However, they’re also using content as a way of understanding their customer. After all, as the business space grows more competitive, businesses that don’t understand their buyers will rapidly lose their loyalty.

Forrester Research is currently building a body of evidence around “insight-driven business”. Forrester believes that fast-growing companies need to innovate based on customer understanding and experience, and AI can make this easier, by delivering unstructured, real-time customer interactions sure to offer value. With AI, you can:

The Success Factors Behind AI in Content Marketing

As new businesses begin to invest in AI approaches, there are some commonalities that can be noticed among successful projects, for instance:

Defined Goals: Early innovators had to make leaps of faith in the AI world without a specific objective. However, as the landscape grows and more opportunities arise, every project can be linked to measurable business outcomes.

Executive sponsorship: Executive sponsorship is key to delivering solutions that really work. Larger organisations often find that to open the right data sets to drive business value, they eventually need an executive sponsor to champion automated marketing approaches.

Available data sets: Most experts agree that mediocre algorithms with a large data set will usually trump a great algorithm with a small data set. Dig into your options, clean what you can, and integrate new data sources.

Team composition: While the focus of most AI is to reduce the need for manual tasks, technology needs to fit within a team that understands the value of that application. Non-technical businesses are beginning to explore the world of AI, but for the meantime, it’s important to ensure that the team fully understands the data it’s given.

Vendor selection: Finally, when it comes to choosing the right AI solutions for content, it’s crucial to make sure that you’re picking the right vendor for your needs. Make sure that you ask about the data sets available, try multiple trials and demo, and push to understand more about each system.